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At least 973 records · Page 54

APOLLO: a facility-scale differentiable virtual accelerator for Fermilab

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or yield additional insights like gradients. The FAST/IOTA facility has been working on implementing and experimentally validating an end-to-end digital twin that is both fast and gradient-aware, allowing for rapid prototyping of new software and experiments with minimal beam time costs. Our framework integrates physics and ML codes for linac and ring simulation through a set of generic interfaces between surrogate and physics-based sections. To reproduce device inputs and outputs, system state is exposed as a deterministic discrete event simulator. Because Fermilab is undergoing control system transition, both EPICS and ACNET frontends are supported. Recently, we have begun transitioning to a new community lattice standard, PALS, as well as developing standardized infrastructure for data ingest and normalization to prepare for model calibration during FAST proton injector commissioning. We discuss implementation details as well as challenges, and future plans to extend modelling to main complex proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗

First Measurement of Differential Charged Current Quasi-Elastic-Like $\nu_{\mu}$ Argon Scattering Cross Sections with the MicroBooNE Detector

Current and future generation neutrino oscillation experiments aim towards a high-precisionmeasurement of the oscillation parameters, which requires an unprecedented understanding ofneutrino-nucleus scattering. Charged-current quasi-elastic (CCQE) scattering is the process inwhich the neutrino produces a charged lepton and removes a single intact nucleon from the nu-cleus without producing any additional particles. For existing and forthcoming accelerator–based neutrino experiments, CCQE interactions are either the dominant process or part of the signal.MicroBooNE is the first liquid argon time projection chamber (LArTPC) commissioned as part ofthe Short Baseline Neutrino (SBN) program at Fermilab and its excellent particle reconstructioncapabilities allow the detection of neutrino interactions using exclusive final states, which will playa crucial role in the success of future kiloton LArTPC detectors such as DUNE. This talk willpresent the first measurement of exclusive νμ-Ar CCQE–like flux integrated total and differentialcross sections using single proton knock–out interactions recorded by the MicroBooNE LArTPCdetector, which has comparable acceptance to deuterium Bubble Chambers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System: Supporting Data

This data contains data from 90-day long incubation study which aimed to look at the soil moisture-texture relationship on soil organic carbon (SOC) cycling. Soils were collected from three distinct soil textures from mixed forests in 2017: sandy (Georgia, 2017-05-01), loamy (Missouri, 2017-06-14) and clayey (Texas, December 2017) were incubated at different soil moisture levels (air-dried, 25% water holding capacity (WHC), 50% WHC, 100% WHC and 175% WHC) at room temperature for a period of 90 days. Files contain microbial respiration, active and slow SOC pools, and their respective mineralization rates, extractable organic carbon (C), and C-acquiring extracellular enzymes. Findings from these data were used in Singh et al. (2021). This study aimed to examine the interactive effect of soil moisture and texture on SOC mineralization. Soil samples of three distinct textures (sandy, loamy, and clayey) were collected from mixed forests of Georgia, Missouri, and Texas, respectively. Soil cores of 5 cm diameter were collected from numerous random locations at each site from 0-15 cm depth after scraping the litter layer and mixed thoroughly to obtain a composite sample per site. Three additional soil cores were collected to determine the WHC using pressure plate extractors. Soil samples were composited, and triplicate soil samples were incubated in mason jars for a period of 90 days at room temperature under different moisture regimes: air dried, 25% WHC, 50% WHC, at WHC and 100% saturation. Soil respiration was measured weekly, and destructive sampling was conducted at 1, 15, 60, and 90 days to determine extractable organic C, C acquiring enzyme activity, and active and slow SOC pools with their respective mineralization rates. The C acquiring enzyme activity was the total activity of α-glucosidase, β-glucosidase, cellobiohydrolase, and β-xylosidase enzymes. Gas samples for microbial respiration measurements were collected from headspace of incubation jars through the sampling ports on the lids and then analyzed using a Shimadzu Gas Chromatograph (GC-2014). Prior to sampling, the vials were evacuated. Blank correction was also done by collecting gas samples from empty incubation jars. Double pool exponential decay model was used in SigmaPlot to determine the active and slow SOC pools and their mineralization rates (Farrar et al., 2012; Jagadamma et al., 2014). The C-acquiring extracellular enzymes were measured using the microplate method by German et al., (2011). Microbial community structure was determined using the phospholipid fatty acid (PLFA) and neutral lipid fatty acid (NLFA) analyses (Buyer and Sasser, 2012). This dataset has seven data files provided in comma-separate (*.csv) format. Additional metadata are provided: seven data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

Carbon acquiring enzyme activity↗

16s Amplicon Analysis of Soil Data for Interactive effects of depth and differential irrigation on soil microbiome composition and functioning

Genomic DNA was isolated from soil and rhizosphere samples using the Zymo Quick-DNA fecal/soil microbe miniprep kit (catalog no. D6010) according to the manufacturer’s instructions (Zymo Research; Irvine, CA) with the modification of eluting in 100 uL elution buffer. Sample concentrations were quantified using the Qubit dsDNA HS assay kit (Thermo Fisher). For rhizosphere samples only, DNA was subsequently purified using Zymo’s ZR-96 DNA Clean & Concentrator kit (catalog no. D4024) to account for low DNA concentrations of these samples. . In each replicate block, there were five drip irrigation treatments (T1 = 100% normal irrigation, T2 = 56.25%, T3 = 37.5%, T4 = 18.75% and T5=no irrigation. On July 20, the strength of the drought treatments was increased: T1 remained at 100%, whereas T2 changed from 75% to 56.25%, T2 changed from 50% to 37.5%, and T4 changed from 25% to 18.75%. Sequencing was performed as described previously (Naylor, Fansler, et al. 2020). Sequences were amplified on the MiSeq platform (Illumina, San Diego, CA) using 16S primers (515F and 806R) specific to the V4 region. Raw sequence data was processed with the pipeline Hundo for amplicon quality control and annotation. Downstream statistical analyses on 16S datasets were performed using the program R and the packages ‘phyloseq’ and ‘vegan’.

Soil microbiome, metatranscriptomics↗

Metatransciptomic Analysis Data for Interactive effects of depth and differential irrigation on soil microbiome composition and functioning

RNA was collected from soil at different depths and after three different levels of irrigation T1 100% of normal field irrigation, T4: 18.75% or normal irrigation and T5: unirrigated controls. Total RNA was isolated using the Zymo Quick-RNA fecal/soil microbe miniprep (catalog no. R2040), incorporating the DNase I treatment using Zymo’s DNase I kit (catalog no. E1010). To increase the yield of RNA, we modified the manufacturer’s instructions by first doubling the amount of soil per extraction (from 0.25 g to 0.5 g) and by performing extractions in triplicate before pooling separate extractions together. Certain soil samples (largely those from deeper soil layers) had low yield (< 100 ng per extraction) so additional rounds of extraction were performed to obtain sufficient RNA. RNA concentration was assessed using a Qubit RNA HS assay kit (Thermo Fisher) and RNA quality was determined using an Agilent 2100 BioAnalyzer (Agilent; Santa Clara, CA). The resultant RNA samples were then sequenced by GENEWIZ using Illumina technology (GENEWIZ; South Plainfield, NJ). Sequences were then aligned to a soil metagenome previously obtained from the same site using the Burrows-Wheeler aligner (BWA). SAM files were then converted to raw counts using HTSeq.

Soil microbiome, metatranscriptomics↗

Differential Organic Carbon Mineralization Responses to Soil Moisture in Three Different Soil Orders Under Mixed Forested System

Soil microbial respiration is one of the largest sources of carbon (C) emissions to the atmosphere in terrestrial ecosystems, which is strongly dependent on multiple environmental variables including soil moisture. Soil moisture content is strongly dependent on soil texture, and the combined effects of texture and moisture on microbial respiration are complex and less explored. Therefore, this study examines the effects of soil moisture on the mineralization of soil organic C Soil organic carbon in three different soils, Ultisol, Alfisol and Vertisol, collected from mixed forests of Georgia, Missouri, and Texas, United States , respectively. A laboratory microcosm experiment was conducted for 90 days under different moisture regimes. Soil respiration was measured weekly, and destructive harvests were conducted at 1, 15, 60, and 90 days after incubation to determine extractable organic C (EOC), phospholipid fatty acid based microbial community, and C-acquiring hydrolytic extracellular enzyme activities (EEA). The highest cumulative respiration in Ultisol was observed at 50% water holding capacity (WHC), in Alfisol at 100% water holding capacity, and in Vertisol at 175% WHC. The trends in Extractable Organic Carbon were opposite to that of cumulative microbial respiration as the moisture levels showing the highest respiration showed the lowest EOC concentration in all soil types. Also, extracellular enzyme activities increased with increase in soil moisture in all soils, however, respiration and EEA showed a decoupled relationship in Ultisol and Alfisol soils. Soil moisture differences did not influence microbial community composition.

54 ENVIRONMENTAL SCIENCES↗

Ectomycorrhizal and Dark Septate Fungal Associations of Pinyon Pine Are Differentially Affected by Experimental Drought and Warming

Changing climates can cause shifts in temperature and precipitation, resulting in warming and drought in some regions. Although each of these factors has been shown to detrimentally affect forest ecosystems worldwide, information on the impacts of the combined effects of warming and drought is lacking. Forest trees rely on mutualistic root-associated fungi that contribute significantly to plant health and protection against climate stresses. We used a six-year, ecosystem-scale temperature and precipitation manipulation experiment targeted to simulate the climate in 2100 in the Southwestern United States to quantify the effects of drought, warming and combined drought and warming on the root colonization (abundance), species composition and diversity of ectomycorrhizal fungi (EMF), and dark septate fungal endophytes in a widespread woodland tree, pinyon pine (Pinus edulis E.). Our results show that pinyon shoot growth after 6 years of these treatments was reduced more by drought than warming. The combined drought and warming treatment reduced the abundance and diversity of EMF more than either treatment alone. Individual ectomycorrhizal fungal taxa, including the drought tolerant Cenococcum geophilum, were present in all treatments but the combined drought and warming treatment. The combined drought and warming treatment also reduced the abundance of dark septate endophytes (DSE), but did not affect their diversity or species composition. The current year shoot growth of the trees correlated positively with ectomycorrhizal fungal diversity, highlighting the importance of diversity in mutualistic relationships to plant growth. Our results suggest that EMF may be more important than DSE to aboveground growth in P. edulis, but also more susceptible to the negative effects of combined climate stressors.

59 BASIC BIOLOGICAL SCIENCES↗

Engineered Cell Line Imaging Assay Differentiates Pathogenic from Non-Pathogenic Bacteria

Cell culture systems have greatly expanded our understanding of how bacterial pathogens target signaling pathways to manipulate the host and cause infection. Advances in genetic engineering have allowed for the creation of fluorescent protein readouts within signaling pathways, but these techniques have been underutilized in pathogen biology. Here, we genetically engineered a lung cell line with fluorescent reporters for extracellular signal-related kinase (ERK) and the downstream transcription factor FOS-related antigen 1 (Fra1) and evaluated signaling after inoculation with pathogenic and non-pathogenic bacteria. Cells were inoculated with 100 colony-forming units of Acinetobacter baylyi, Klebsiella pneumoniae, Pseudomonas aeruginosa, Streptococcus agalactiae, or Staphylococcus epidermidis and imaged in a multi-mode reader. The alamarBlue cell viability assay was used as a reference test and showed that pathogenic P. aeruginosa induced significant (p < 0.05) cell death after 8 h in both wild-type and engineered cell lines compared to non-pathogenic S. epidermidis. In engineered cells, we found that Fra1 signaling was disrupted in as little as 4 h after inoculation with bacterial pathogens compared to delayed disruption in signaling by non-pathogenic S. epidermidis. Overall, we demonstrate that low levels of pathogenic versus non-pathogenic bacteria can be rapidly and sensitively screened based on ERK-Fra1 signaling

59 BASIC BIOLOGICAL SCIENCES↗

An Accurate Vegetation and Non-Vegetation Differentiation Approach Based on Land Cover Classification

Accurate vegetation detection is important for many applications, such as crop yield estimation, land cover land use monitoring, urban growth monitoring, drought monitoring, etc. Popular conventional approaches to vegetation detection incorporate the normalized difference vegetation index (NDVI), which uses the red and near infrared (NIR) bands, and enhanced vegetation index (EVI), which uses red, NIR, and the blue bands. Although NDVI and EVI are efficient, their accuracies still have room for further improvement. In this paper, we propose a new approach to vegetation detection based on land cover classification. That is, we first perform an accurate classification of 15 or more land cover types. The land covers such as grass, shrub, and trees are then grouped into vegetation and other land cover types such as roads, buildings, etc. are grouped into non-vegetation. Similar to NDVI and EVI, only RGB and NIR bands are needed in our proposed approach. If Laser imaging, Detection, and Ranging (LiDAR) data are available, our approach can also incorporate LiDAR in the detection process. Results using a well-known dataset demonstrated that the proposed approach is feasible and achieves more accurate vegetation detection than both NDVI and EVI. In particular, a Support Vector Machine (SVM) approach performed 6% better than NDVI and 50% better than EVI in terms of overall accuracy (OA).

54 ENVIRONMENTAL SCIENCES↗

A Differential Measurement of Circumstellar Extinction for AA Tau’s 2011 Dimming Event

AA Tau is a classical T Tauri star with a highly inclined, warped circumstellar disk. For decades, AA Tau exhibited photometric and spectroscopic variabilities that were successfully modeled as occultations of the primary star by circumstellar material. In 2011, AA Tau entered an extended faint state, presumably due to enhanced levels of circumstellar dust. We use two sets of contemporaneous optical–near-IR (NIR) spectra of AA Tau, obtained in 2008 and 2014 December, to directly measure the wavelength-dependent extinction associated with the dust enhancement driving AA Tau’s 2011 optical fade. Taken alone, AA Tau’s apparent optical–NIR increased extinction curve cannot be fit well with standard extinction laws. At optical wavelengths, AA Tau’s dimming event is consistent with predictions of common extinction models for an increase of A {sub V} = 2, but no such model reproduces AA Tau’s color–color excess at NIR wavelengths. We show that veiling emission accounts for the apparent anomalous NIR extinction: after including this veiling flux, AA Tau’s dimming event is consistent with a standard A {sub V} = 2 extinction law across the full optical–NIR range. We also report an increase in AA Tau’s mid-IR flux since its 2011 fade and suggest that an increase in the height of AA Tau’s inner disk is the most likely explanation for both the IR brightening and the additional extinction along the line of sight. In addition to informing our understanding of AA Tau, this analysis demonstrates that caution should be exercised when inferring extinction (and stellar parameters) from the NIR color–color excess of young stars with measurable NIR veiling fluxes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

On the Utility of Transmission Color Analysis i: Differentiating Super-Earths and Sub-Neptunes

The majority of exoplanets found to date have been discovered via the transit method, and transmission spectroscopy represents the primary method of studying these distant worlds. Currently, in-depth atmospheric characterization of transiting exoplanets entails the use of spectrographs on large telescopes, requiring significant observing time to study each planet. Previous studies have demonstrated trends for solar system worlds using color–color photometry of reflectance spectra, as well as trends within transmission spectra for hot Jupiters. Building on these concepts, we have investigated the use of transmission color photometric analysis for efficient, coarse categorization of exoplanets and for assessing the nature of these worlds, with a focus on resolving the bulk composition degeneracy to aid in discriminating super-Earths and sub-Neptunes. We present our methodology and first results, including spectrum models, model comparison frameworks, and wave band selection criteria. We present our results for different transmission “color” metrics, filter selection methods, and numbers of filters. Assuming noise-free spectra of isothermal atmospheres in chemical equilibrium, with our pipeline, we are able to constrain atmospheric mean molecular weight in order to distinguish between super-Earth and sub-Neptune atmospheres with >90% overall accuracy using specific low-resolution filter combinations, . We also found that increasing the number of filters does not substantially impact this performance. This method could allow for broad characterization of large numbers of planets much more efficiently than current methods permit, enabling population- and system-level studies. Additionally, data collected via this method could inform follow-up observing time by large telescopes for more detailed studies of worlds of interest.

47 OTHER INSTRUMENTATION↗